Multi-organ segmentation of abdominal structures from non-contrast and contrast enhanced CT images

Manually delineating upper abdominal organs at risk (OARs) is a time-consuming task. To develop a deep-learning-based tool for accurate and robust auto-segmentation of these OARs, forty pancreatic cancer patients with contrast-enhanced breath-hold computed tomographic (CT) images were selected. We t...

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Detalles Bibliográficos
Autores principales: Yu, Cenji, Anakwenze, Chidinma P., Zhao, Yao, Martin, Rachael M., Ludmir, Ethan B., S.Niedzielski, Joshua, Qureshi, Asad, Das, Prajnan, Holliday, Emma B., Raldow, Ann C., Nguyen, Callistus M., Mumme, Raymond P., Netherton, Tucker J., Rhee, Dong Joo, Gay, Skylar S., Yang, Jinzhong, Court, Laurence E., Cardenas, Carlos E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646761/
https://www.ncbi.nlm.nih.gov/pubmed/36351987
http://dx.doi.org/10.1038/s41598-022-21206-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646761/
https://www.ncbi.nlm.nih.gov/pubmed/36351987
http://dx.doi.org/10.1038/s41598-022-21206-3

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